使用SQLAlchemy使用pandas写入MySQL数据库

Question

尝试使用to_sql将pandas数据帧写入MySQL表。以前使用过flavor='mysql'，但是将来会贬值，希望开始过渡到使用SQLAlchemy引擎。

示例代码：

import pandas as pd
import mysql.connector
from sqlalchemy import create_engine

engine = create_engine('mysql+mysqlconnector://[user]:[pass]@[host]:[port]/[schema]', echo=False)
cnx = engine.raw_connection()
data = pd.read_sql('SELECT * FROM sample_table', cnx)
data.to_sql(name='sample_table2', con=cnx, if_exists = 'append', index=False)

读取工作正常，但to_sql有错误：

DatabaseError: Execution failed on sql 'SELECT name FROM sqlite_master WHERE type='table' AND name=?;': Wrong number of arguments during string formatting

为什么它看起来像是在尝试使用sqlite？对于mysql，特别是mysql.connector，正确使用sqlalchemy连接是什么？

我还尝试将引擎作为连接传入，这给了我一个引用no cursor对象的错误。

data.to_sql(name='sample_table2', con=engine, if_exists = 'append', index=False)
>>AttributeError: 'Engine' object has no attribute 'cursor'

Answer 1

使用引擎代替工作的raw_connection()：

import pandas as pd
import mysql.connector
from sqlalchemy import create_engine

engine = create_engine('mysql+mysqlconnector://[user]:[pass]@[host]:[port]/[schema]', echo=False)
data.to_sql(name='sample_table2', con=engine, if_exists = 'append', index=False)

不清楚为什么我昨天试着这么做时，它给了我先前的错误。

Answer 2

或者，使用pymysql包。。。

import pymysql
from sqlalchemy import create_engine
cnx = create_engine('mysql+pymysql://[user]:[pass]@[host]:[port]/[schema]', echo=False)

data = pd.read_sql('SELECT * FROM sample_table', cnx)
data.to_sql(name='sample_table2', con=cnx, if_exists = 'append', index=False)

Answer 3

使用pymysql和sqlalchemy，这适用于Pandas v0.22：

import pandas as pd
import pymysql
from sqlalchemy import create_engine

user = 'yourUserName'
passw = 'password'
host =  'hostName'  # either localhost or ip e.g. '172.17.0.2' or hostname address 
port = 3306 
database = 'dataBaseName'

mydb = create_engine('mysql+pymysql://' + user + ':' + passw + '@' + host + ':' + str(port) + '/' + database , echo=False)

directory = r'directoryLocation'  # path of csv file
csvFileName = 'something.csv'

df = pd.read_csv(os.path.join(directory, csvFileName ))

df.to_sql(name=csvFileName[:-4], con=mydb, if_exists = 'replace', index=False)

"""
if_exists: {'fail', 'replace', 'append'}, default 'fail'
     fail: If table exists, do nothing.
     replace: If table exists, drop it, recreate it, and insert data.
     append: If table exists, insert data. Create if does not exist.
"""